Massimo Caccia

I recently completed my Ph.D. at the Quebec Artificial Intelligence Institute (Mila) under the guidance of Professor Laurent Charlin. My academic journey has been marked by collaborations with globally renowned institutions, including DeepMind, where I worked within the Continual Learning team led by Marc’Aurelio Ranzato, Amazon in Alex Smola’s team, and now at ServiceNow as a visiting researcher. I also had the privilege of contributing to ElementAI before its integration with ServiceNow.   At the heart of my research is the development of algorithms proficient in accumulating and transferring knowledge or skills to enhance generalization across varied tasks. My passion for data and computational efficiency has directed my studies into continual, transfer, and meta-learning, with a particular emphasis on applications spanning vision, language, and reinforcement learning.   In recent times, my research has centered predominantly on the design and development of computer task-solving agents, with a particular emphasis on leveraging the capabilities of Large Language Models (LLMs). These agents, powered by the vast knowledge and adaptability of LLMs, have the potential to autonomously navigate and master a wide array of computer tasks. I am deeply committed to this vision, exploring the full potential of LLM-driven agents in diverse and challenging real-world scenarios. ************************************************* Massimo is a third year PhD student at the Quebec Artificial Intelligence Institute (MILA) and an intern at ElementAI under the supervision of Laurent Charlin and Pau Rodriguez, respectively. He’s interested in algorithms able to accumulate transferable knowledge or skills enabling generalization to future tasks. Consequently, Massimo’s research topics lies in continual learning and meta-learning. His recent work proposes a new and more realistic approach to continual learning at the intersection of both fields.